Co-training is a method for combining labeled and unlabeled data when examples can be thought of as containing two distinct sets of features. It has had a number of practical successes, yet previous theoretical analyses have needed very strong assumptions on the data that are unlikely to be...

In this paper, we investigate the finite sample performance of four kernel-based estimators that are currently available for additive non-parametric regression models—the classic backfitting estimator (CBE), the smooth backfitting estimator, the marginal integration estimator, and two versions...